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99 results for “Computational Models”
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Research ArticleOpen accessIn the abstractApplications of Machine Learning in Building Energy Prediction and SavingsPriyan Rai, Dr. Nabil Nassif, Kevin Eaton, Alexander RodriguesIn a constantly advancing world with growing needs, buildings play in important role in the daily functioning of the society. Developing more and more advanced techniques to optimize the working of these buildings is highly important for a constant growth. Modern computational techniques have opened doors to create advanced models that can utilize efficient techniques to produce highly accurate results. … …Energy Research Journal, Vol. 10, Issue 1 · 15 Mar 2019 · 8,041 accessesView PDFCite
Research ArticleOpen accessIn the abstractInternet of Things and Human Neocortex Inspired Algorithms for the Plant Disease Prediction-Sheath Blight for Paddy PlantThangaraj Ethilu, K. Parthiban, Arockia Jayadhas S et al.Sheath blight disease (Rhizoctonia solani) poses a critical threat to paddy (Oryza sativa) production, causing up to 50% yield losses under conducive environmental conditions. Existing computer vision-based disease detection systems identify infections only after symptom manifestation, while conventional machine learning prediction models suffer from high computational demands, data preprocessing requirements, and noise sensitivity. This research proposes a novel Hierarchical Temporal … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 1,780 accessesView PDFCite
Research ArticleOpen accessIn the abstractIn silico and in vitro Structural Analysis on the Interaction of Calmodulin and Calmodulin-Binding Motif of FKBP35 from Plasmodium knowlesiSazlinawatie Aladin, Cahyo Budiman et al.FK506-binding protein 35 (FKBP35) is a peptidyl-prolyl cis-trans isomerase found in Plasmodium knowlesi, a zoonotic malaria parasite responsible for concerning cases of malaria infection in East Malaysia. This protein contains a segment known as the calmodulin-binding motif (Pk-CBM), which is predicted to facilitate interaction with calmodulin from P. knowlesi (Pk-CaM). Although this interaction is considered promising for future antimalarial drug … …OnLine Journal of Biological Sciences, Vol. 25, Issue 2 · 10 Mar 2025 · 4,857 accessesView PDFCite
Research ArticleOpen accessIn the abstractDifferSqueezeNet: A Leaner Defect Detection ModelJose Joao Manrique Franco, Marcelo RudekIn the industrial environment, the inherent limitations of manual inspection have caused the ascent of automated computer vision systems that aim to match or surpass human performance. In this context, the artificial intelligence field has been interested in defect detection with the creation of many machine learning techniques, focusing on Unsupervised and Semi-supervised learning methods. Since most of these methods … …Journal of Computer Science, Vol. 21, Issue 3 · 4 Feb 2025 · 5,734 accessesView PDFCite
Review ArticleOpen accessIn the abstractHybrid Machine Learning Framework with Data Analytics Model for Privacy-Preserved Intelligent Predictive Maintenance in Healthcare IoTArun Ganji, D. Usha, P.S. RajakumarFederated Learning (FL) is a cutting-edge approach for developing machine learning (ML) models using distributed datasets while preserving data privacy and ownership. FL is particularly suited for Internet of Things (IoT) networks due to its decentralized nature, which supports In-Edge AI and maintains data locality. However, FL's complexity poses challenges in analyzing system health, making it crucial to develop robust … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,830 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptivity in Role-Based Access Control During Stochastic Situations: A Comprehensive Study between Graph and Relational DatabasesKriti Srivastava, Dhruv Jain, Aarya Kamdar et al.Role-based control is straightforward to implement in static systems where there are specific policies for role and resource mapping. The main challenge is faced in dynamic and unpredictable systems with erratic workflows. Conventional methods prove to be inadequate in dynamic environments. Over the Years methods suggested include probabilistic, machine learning, ontology, and decision tree models to improve the adaptability. However, … …Journal of Computer Science, Vol. 20, Issue 12 · 18 Nov 2024 · 5,378 accessesView PDFCite
Research ArticleOpen accessIn the abstractLogistic Regression with Multi-Connected WeightsAvazjon Marakhimov Rakhimovich, Kabul Khudaybergenov Kadirbergenovich, Zahriddin Muminov Ishkobilovich, Kudaybergenov Jabbarbergen KadirbergenovichResults of current research in biological and cognitive science reveal that neuronal interactions predominantly depend on neurotransmitters for signaling and sending information between neurons. Furthermore, a specific neuron that is connected to the next neuron transmits or sends multiple neurotransmitters in parallel ways, where each neurotransmitter has specific functional roles. Based on these results, a new type of logistic regression … …Journal of Computer Science, Vol. 20, Issue 9 · 4 Jul 2024 · 5,064 accessesView PDFCite
Research ArticleOpen accessIn the abstractQuantization of Map-Based Neuronal Model for Embedded Simulations of Neurobiological Networks in Real-TimeNikolai F. Rulkov, Ariel Mark Hunt, Peter N. Rulkov, Andrey G. MaksimovThe discreet-time (map-based) approach to modeling nonlinear dynamics of spiking and spiking-bursting activity of neurons has demonstrated its very high efficiency in simulations of neuro-biologically realistic behavior both in large-scale network models for brain activity studies and in real-time operation of Central Pattern Generator network models for biomimetic robotics. This paper studies the next step in improving the model computational … …American Journal of Engineering and Applied Sciences, Vol. 9, Issue 4 · 9 Nov 2016 · 8,778 accessesView PDFCite